Delineation of ECT images using global constraints and dynamic programming

A model-based delineation algorithm is presented. It is a flexible model fitting algorithm, approaching contour detection as an optimization problem. An objective function is introduced, which depends not only on local contour features, but also on a global shape constraint. The latter is implemented as the similarity to the instance of a parametric shape model. The algorithm optimizes both the contour points and the parameters of the model. As a result, both global and local characteristics of the contour are determined as a compromise between photometric data and prior knowledge. The method was applied to myocardial perfusion SPECT images, to delineate the entire left ventricle (endocardium and epicardium), including possible regions of reduced perfusion. By adapting the balance between the image data and the shape model, images with different characteristics can be processed, including Thallium-201 and MIBI scans.     

Numerical calculations of the capacitance of linearly graded Si p-n junctions

Exact calculations are made of the capacitance of linearly graded Si p-n junctions, taking the influence of electrons and holes into account. The results agree well with the experimental data for gradients of less than 1022cm?4. The discrepancies for gradients larger than 1022cm?4 are probably due an interface-state mechanism.     

Morphologic and functional changes in the unilateral 6-hydroxydopamine lesion rat model for Parkinson’s disease discerned with μSPECT and quantitative MRI

Object

In the present study, we aimed to evaluate the impact of neurodegeneration of the nigrostriatal tract in a rodent model of Parkinson’s disease on the different MR contrasts (T₂, T₁, CBF and CBV) measured in the striatum.

Material and methods

Animals were injected with 6-hydroxydopamine (6OHDA) in the substantia nigra resulting in massive loss of nigrostriatal neurons and hence dopamine depletion in the ipsilateral striatum. Using 7T MRI imaging, we have quantified T₂, T₁, CBF and CBV in the striata of 6OHDA and control rats. To validate the lesion size, behavioral testing, dopamine transporter μSPECT and tyrosine hydroxylase staining were performed.

Results

No significant differences were demonstrated in the absolute MRI values between 6OHDA animals and controls; however, 6OHDA animals showed significant striatal asymmetry for all MRI parameters in contrast to controls.

Conclusions

These PD-related asymmetry ratios might be the result of counteracting changes in both intact and affected striatum and allowed us to diagnose PD lesions. As lateralization is known to occur also in PD patients and might be expected in transgenic PD models as well, we propose that MR-derived asymmetry ratios in the striatum might be a useful tool for in vivo phenotyping of animal models of PD.     

Evaluation of three MRI-based anatomical priors for quantitative PET brain imaging

In emission tomography, image reconstruction and therefore also tracer development and diagnosis may benefit from the use of anatomical side information obtained with other imaging modalities in the same subject, as it helps to correct for the partial volume effect. One way to implement this, is to use the anatomical image for defining the a priori distribution in a maximum-a-posteriori (MAP) reconstruction algorithm. In this contribution, we use the PET-SORTEO Monte Carlo simulator to evaluate the quantitative accuracy reached by three different anatomical priors when reconstructing positron emission tomography (PET) brain images, using volumetric magnetic resonance imaging (MRI) to provide the anatomical information. The priors are: 1) a prior especially developed for FDG PET brain imaging, which relies on a segmentation of the MR-image (Baete , 2004); 2) the joint entropy-prior (Nuyts, 2007); 3) a prior that encourages smoothness within a position dependent neighborhood, computed from the MR-image. The latter prior was recently proposed by our group in (Vunckx and Nuyts, 2010), and was based on the prior presented by Bowsher (2004). The two latter priors do not rely on an explicit segmentation, which makes them more generally applicable than a segmentation-based prior. All three priors produced a compromise between noise and bias that was clearly better than that obtained with postsmoothed maximum likelihood expectation maximization (MLEM) or MAP with a relative difference prior. The performance of the joint entropy prior was slightly worse than that of the other two priors. The performance of the segmentation-based prior is quite sensitive to the accuracy of the segmentation. In contrast to the joint entropy-prior, the Bowsher-prior is easily tuned and does not suffer from convergence problems.     

Acceleration of maximum likelihood reconstruction, using frequency amplification and attenuation compensation

Algorithms that calculate maximum likelihood (ML) and maximum a posteriori solutions using expectation-maximization have been successfully applied to SPECT and PET. These algorithms are appealing because of their solid theoretical basis and their guaranteed convergence. A major drawback is the slow convergence, which results in-long processing times. The authors present 2 new heuristic acceleration methods for maximum likelihood reconstruction of ECT images. The first method incorporates a frequency-dependent amplification in the calculations, to compensate for the low pass filtering of the backprojection operation. In the second method, an amplification factor is incorporated that suppresses the effect of attenuation on the updating factors. Both methods are compared to the 1-dimensional line search method proposed by Lewitt. All 3 methods accelerate the ML algorithm. On the authors' test images, Lewitt's method produced the strongest acceleration of the three individual methods. However, the combination of the frequency amplification with the line search method results in a new algorithm with still better performance. Under certain conditions, an effective frequency amplification can be already achieved by skipping some of the calculations required for ML.     

SLAC: Statistical total lesion metabolic activity computation by fuzzy unsupervised learning of PET images

Accurate lesion metabolic response estimation is imperative for efficient tumor staging and follow-up studies. Positron emission tomography (PET) successfully images the lesion metabolic activity. Nonetheless, on course of accurate delineation, chances are high to end up with activity underestimation as, due to the limited resolution, the PET images suffer from partial volume effects. Recently, PET images were modeled as a fuzzy mixture to delineate lesions accurately. We extend this work by proposing a statistical lesion activity computation (SLAC) approach to robustly estimate the total lesion activity (TLA) directly from the modeled partial volume mixtures, without an explicit delineation. To evaluate the proposed method, PET scans of phantoms containing spherical and non-spherical lesions with increased activity uptake were simulated. The PET images were reconstructed with the standard clinically used maximum likelihood expectation maximization and an edge preserving maximum a posteriori (MAP) algorithm, both with resolution recovery. From these images, the TLA was estimated in each lesion using the proposed method and compared to the TLA estimation in the tumor delineations obtained with three state-of-the-art PET delineation schemes. SLAC outperformed TLA estimation via tumor delineation and showed robust against variation in reconstruction parameters. With reference to the ground truth knowledge, SLAC gives median $\delta $ TLA $~\approx $  5 % for spherical lesions. For more realistic non-spherical lesions, median $\delta $ TLA $~\approx $  15 %.     

Clinical evaluation of a custom-made toric soft lens.

PURPOSE: The fitting of toric soft contact lenses is often complicated by interference between the toric optics and the geometry need to stabilise the lens on the eye. The use of a spherical trial lens to determine the parameters of a toric soft contact lens can lead to unintended positioning and movement of the lens ordered. The purpose of this study was to evaluate clinically the success. PURPOSE: The fitting of toric soft contact lenses is often complicated by interference between the toric optics and the geometry needed. METHOD: The design of the lenses used was such that optical correction and stabilisation were separated. The lenses had a back tonic surface limited to the central optical zone and base down prism stabilisation in the periphery. The empirical system used corneal radii, spectacle refraction and horizontal visible iris diameter as lens design parameters. RESULTS: This multi-centre trial, comprised of 105 patients (193 eyes), revealed an overall success rate of 86%. The total number of lenses ordered to achieve success was 1.46 per eye in new patients and 1.69 per eye in patients who were failures with other toric soft lenses. In 14% of the cases success could not be achieved despite ordering several lenses (up to 4 lenses/eye). Many of these patients (60%) were also failures with other toric soft lenses. CONCLUSION: It is concluded that in new patients successful toric soft contact lens fitting can be achieved with an empirically based method. When refitting former toric soft lens failures, we recommend discontinuation after two further unsuccessful fittings.     

PET scan predicts recovery of left ventricular function after coronary artery bypass operation

BACKGROUND: Viable but hypocontractile myocardium can show functional improvement after revascularization (hibernation). It is sometimes difficult, however, to predict viability and recovery in patients with severe left ventricular function. This study sought to identify possible predictive factors of recovery of cardiac function after revascularization in patients with three-vessel disease. METHODS: Positron emission tomography (fluoro-18-deoxyglucose uptake for metabolism; nitrogen 13-labeled ammonia for flow) and equilibrium-gated nuclear angiography (for the global ejection fraction) were performed in 59 patients with three-vessel disease before and after undergoing coronary artery bypass grafting. The positron emission tomographic data were expressed as match normal (flow and metabolism normal), mismatch (low flow, high metabolism), match viable (moderate decrease in flow and metabolism), and match necrosis (low flow and metabolism). RESULTS: Stepwise logistic regression analysis showed that only mismatch regions played a significant role in predicting postoperative improvement in function (p = 0.019). There were 1.7 +/- 1.5 mismatch regions in 31 patients who showed an improvement in their ejection fraction (0.47 +/- 0.14 versus 0.58 +/- 0.11; mean +/- standard deviation) versus 0.8 +/- 1.0 mismatch regions (p = 0.017) in patients who did not show recovery. There was more pronounced functional improvement with increasing numbers of mismatch regions, and patients with at least one mismatch region had a high likelihood of recovery (p < 0.001). In patients with a very low preoperative ejection fraction and two or more mismatch regions, there was early significant recovery (0.27 +/- 0.08 versus 0.46 +/- 0.06; p = 0.009). CONCLUSIONS: At least one mismatch region must be present for there to be a postoperative functional benefit. When a low left ventricular ejection fraction is associated with mismatch, early recovery is substantial.